Lung adenocarcinoma (LUAD) is a global malignancy with significant chemoresistance impacting patient prognosis. The pro-tumorigenic role of hyaluronan-mediated motility receptor (HMMR) in LUAD is recognized. This study was designed to investigate the underlying mechanisms by which HMMR affects chemoresistance in LUAD. Bioinformatics presented the expression patterns of HMMR in LUAD patients and the association between HMMR levels and patient survival, followed by qRT-PCR to verify HMMR expression in LUAD tissues and cells. Further, bioinformatics was leveraged to identify the signaling pathways enriched by HMMR and its relevance to glycolytic genes, we also analyzed changes in the glycolytic activity of LUAD cells by manipulating HMMR expression. Stemness was evaluated through cell aggregation assays and Western blot, and drug responsiveness was gauged using CCK-8 assays, alongside flow cytometry for apoptosis analysis. HMMR was highly expressed in LUAD tissues and cells, and this overexpression correlated with poorer prognoses in patients. GSEA showed that HMMR was notably enriched in the glycolysis and gluconeogenesis pathways, correlating positively with the expression of key glycolytic genes. Cellular experiments confirmed that HMMR knockdown notably suppressed aerobic glycolysis in LUAD cells. Moreover, overexpression of HMMR could further enhance the stemness and cisplatin resistance of LUAD cells by stimulating glycolysis. In brief, this study has validated that high levels of HMMR in LUAD are predictive of poor patient prognosis, and that overexpression of HMMR can catalyze aerobic glycolysis, thus promoting stemness and chemoresistance in LUAD cells. Thus, HMMR could be a target for improving chemosensitivity in LUAD.

Lung adenocarcinoma (LUAD) is a global malignancy with significant chemoresistance impacting patient prognosis. The pro-tumorigenic role of hyaluronan-mediated motility receptor (HMMR) in LUAD is recognized. This study was designed to investigate the underlying mechanisms by which HMMR affects chemoresistance in LUAD. Bioinformatics presented the expression patterns of HMMR in LUAD patients and the association between HMMR levels and patient survival, followed by qRT-PCR to verify HMMR expression in LUAD tissues and cells. Further, bioinformatics was leveraged to identify the signaling pathways enriched by HMMR and its relevance to glycolytic genes, we also analyzed changes in the glycolytic activity of LUAD cells by manipulating HMMR expression. Stemness was evaluated through cell aggregation assays and Western blot, and drug responsiveness was gauged using CCK-8 assays, alongside flow cytometry for apoptosis analysis. HMMR was highly expressed in LUAD tissues and cells, and this overexpression correlated with poorer prognoses in patients. GSEA showed that HMMR was notably enriched in the glycolysis and gluconeogenesis pathways, correlating positively with the expression of key glycolytic genes. Cellular experiments confirmed that HMMR knockdown notably suppressed aerobic glycolysis in LUAD cells. Moreover, overexpression of HMMR could further enhance the stemness and cisplatin resistance of LUAD cells by stimulating glycolysis. In brief, this study has validated that high levels of HMMR in LUAD are predictive of poor patient prognosis, and that overexpression of HMMR can catalyze aerobic glycolysis, thus promoting stemness and chemoresistance in LUAD cells. Thus, HMMR could be a target for improving chemosensitivity in LUAD.

Lung adenocarcinoma (LUAD) is a global malignancy with significant chemoresistance impacting patient prognosis. The pro-tumorigenic role of hyaluronan-mediated motility receptor (HMMR) in LUAD is recognized. This study was designed to investigate the underlying mechanisms by which HMMR affects chemoresistance in LUAD. Bioinformatics presented the expression patterns of HMMR in LUAD patients and the association between HMMR levels and patient survival, followed by qRT-PCR to verify HMMR expression in LUAD tissues and cells. Further, bioinformatics was leveraged to identify the signaling pathways enriched by HMMR and its relevance to glycolytic genes, we also analyzed changes in the glycolytic activity of LUAD cells by manipulating HMMR expression. Stemness was evaluated through cell aggregation assays and Western blot, and drug responsiveness was gauged using CCK-8 assays, alongside flow cytometry for apoptosis analysis. HMMR was highly expressed in LUAD tissues and cells, and this overexpression correlated with poorer prognoses in patients. GSEA showed that HMMR was notably enriched in the glycolysis and gluconeogenesis pathways, correlating positively with the expression of key glycolytic genes. Cellular experiments confirmed that HMMR knockdown notably suppressed aerobic glycolysis in LUAD cells. Moreover, overexpression of HMMR could further enhance the stemness and cisplatin resistance of LUAD cells by stimulating glycolysis. In brief, this study has validated that high levels of HMMR in LUAD are predictive of poor patient prognosis, and that overexpression of HMMR can catalyze aerobic glycolysis, thus promoting stemness and chemoresistance in LUAD cells. Thus, HMMR could be a target for improving chemosensitivity in LUAD.

Lung adenocarcinoma (LUAD) is a global malignancy with significant chemoresistance impacting patient prognosis. The pro-tumorigenic role of hyaluronan-mediated motility receptor (HMMR) in LUAD is recognized. This study was designed to investigate the underlying mechanisms by which HMMR affects chemoresistance in LUAD. Bioinformatics presented the expression patterns of HMMR in LUAD patients and the association between HMMR levels and patient survival, followed by qRT-PCR to verify HMMR expression in LUAD tissues and cells. Further, bioinformatics was leveraged to identify the signaling pathways enriched by HMMR and its relevance to glycolytic genes, we also analyzed changes in the glycolytic activity of LUAD cells by manipulating HMMR expression. Stemness was evaluated through cell aggregation assays and Western blot, and drug responsiveness was gauged using CCK-8 assays, alongside flow cytometry for apoptosis analysis. HMMR was highly expressed in LUAD tissues and cells, and this overexpression correlated with poorer prognoses in patients. GSEA showed that HMMR was notably enriched in the glycolysis and gluconeogenesis pathways, correlating positively with the expression of key glycolytic genes. Cellular experiments confirmed that HMMR knockdown notably suppressed aerobic glycolysis in LUAD cells. Moreover, overexpression of HMMR could further enhance the stemness and cisplatin resistance of LUAD cells by stimulating glycolysis. In brief, this study has validated that high levels of HMMR in LUAD are predictive of poor patient prognosis, and that overexpression of HMMR can catalyze aerobic glycolysis, thus promoting stemness and chemoresistance in LUAD cells. Thus, HMMR could be a target for improving chemosensitivity in LUAD.

Lung adenocarcinoma (LUAD) is a global malignancy with significant chemoresistance impacting patient prognosis. The pro-tumorigenic role of hyaluronan-mediated motility receptor (HMMR) in LUAD is recognized. This study was designed to investigate the underlying mechanisms by which HMMR affects chemoresistance in LUAD. Bioinformatics presented the expression patterns of HMMR in LUAD patients and the association between HMMR levels and patient survival, followed by qRT-PCR to verify HMMR expression in LUAD tissues and cells. Further, bioinformatics was leveraged to identify the signaling pathways enriched by HMMR and its relevance to glycolytic genes, we also analyzed changes in the glycolytic activity of LUAD cells by manipulating HMMR expression. Stemness was evaluated through cell aggregation assays and Western blot, and drug responsiveness was gauged using CCK-8 assays, alongside flow cytometry for apoptosis analysis. HMMR was highly expressed in LUAD tissues and cells, and this overexpression correlated with poorer prognoses in patients. GSEA showed that HMMR was notably enriched in the glycolysis and gluconeogenesis pathways, correlating positively with the expression of key glycolytic genes. Cellular experiments confirmed that HMMR knockdown notably suppressed aerobic glycolysis in LUAD cells. Moreover, overexpression of HMMR could further enhance the stemness and cisplatin resistance of LUAD cells by stimulating glycolysis. In brief, this study has validated that high levels of HMMR in LUAD are predictive of poor patient prognosis, and that overexpression of HMMR can catalyze aerobic glycolysis, thus promoting stemness and chemoresistance in LUAD cells. Thus, HMMR could be a target for improving chemosensitivity in LUAD.

C-Glycosylation is one of the modifications of plant secondary metabolites,which can increase the stability,bioavailability,water solubility and biological activities.Flavonoid C-glycosides,as one of the most important plant secondary metabolites,exhibit important biological activities in regulating plant growth and development,resisting pests and diseases,resisting ultraviolet radiation,and antibacterial etc.Generally,this kind of such compounds are biosynthesized by flavonoids reacting with UDP-Glucose and other nucleoside diphosphates catalyzed by C-glycosyltransferase(CGT).This paper reviews the literature reports on the biosynthesis of flavonoid C-glycosides catalyzed by CGT in recent years,and discusses three strategies for its biosynthesis from the perspectives of raw material flavonoids,flavonoid O-glycosides and flavonoid biosynthetic pathways.Among them,the direct or indirect synthesis of flavonoid C-glycosides using flavonoids as raw materials is the most common synthesis strategy,and the classification,plant origin and catalytic function of various CGTs reported recently were also summarized.

A deep learning-based model for automatic diagnosis and classification of adolescent idiopathic scoliosis has been constructed.This model mainly included key points detection and Cobb angle measurement.748 full-length standing spinal X-ray images were retrospectively collected,of which 602 images were used to train and validate the model,and 146 images were used to test the model performance.The results showed that the model had good diagnostic and classification performance,with an accuracy of 94.5%.Compared with experts'measurement,94.9%of its Cobb angle measurement results were within the clinically acceptable range.The average absolute difference was 2.1°,and the consistency was also excellent(r2≥0.9552,P<0.001).In the future,this model could be applied clinically to improve doctors'diagnostic efficiency.

Objective A deep learning-based method for evaluating the quality of pediatric pelvic X-ray images is proposed to construct a diagnostic model and verify its clinical feasibility.Methods Three thousand two hundred and forty-seven children with anteroposteric pelvic radiographs are retrospectively collected and randomly divided into training datasets,validation datasets and test datasets.Artificial intelligence model is conducted to evaluate the reliability of quality control model.Results The diagnostic accuracy,area under ROC curve,sensitivity and specificity of the model are 99.4%,0.993,98.6%and 100.0%,respectively.The 95%consistency limit of the pelvic tilt index of the model is-0.052-0.072.The 95%consistency threshold of pelvic rotation index is-0.088-0.055.Conclusion This is the first attempt to apply AI algorithm to the quality assessment of children's pelvic radiographs,and has significantly improved the diagnosis and treatment status of DDH in children.

Objective:To determine the expression of transglutaminase 2 (TGM2) in peripheral blood mononuclear cells (PBMCs) from patients with atopic dermatitis (AD), and to analyze its correlation with AD-related inflammatory factors and disease severity.Methods:A total of 29 AD patients and 15 healthy controls were collected from the First Affiliated Hospital of Fujian Medical University from July 2020 to January 2021. Ten milliliters of peripheral blood samples were collected from each subject, so was the clinical information, including age, gender, course of disease, eosinophil counts, basophil counts, total IgE levels, Scoring AD index (SCORAD), etc. PBMCs were isolated by density gradient centrifugation. Fluorescence-based quantitative PCR was performed to determine the mRNA expression of TGM2 and AD-related inflammatory factors (interleukin [IL]-1β, IL-4, IL-6, IL-8, IL-10, IL-13, IL-17, thymic stromal lymphopoietin [TSLP], P2RX7 [purinergic receptor P2X, ligand-gated ion channel, 7], etc.) in PBMCs from 29 AD patients and 15 healthy controls, and flow cytometry to determine TGM2 protein expression on PBMCs. Mann-Whitney U test was used to analyze differences between groups, and Spearman correlation analysis to evaluate the correlation. Results:The relative mRNA expression of TGM2 in PBMCs did not differ between the AD group and control group ( M[ Q1, Q3]: 0.509 [0.325, 0.958] vs. 0.475 [0.328, 1.051], U = 210.50, P = 0.872). Compared with the control group, the AD group showed significantly decreased IL-4 mRNA expression (0.171[0.049, 0.449] vs. 0.824 [0.397, 1.378], P < 0.001), but significantly increased mRNA expression of IL-8 and IL-13 ( P = 0.011, 0.006, respectively). Spearman correlation analysis showed that the mRNA expression level of TGM2 in PBMCs was positively correlated with the mRNA expression levels of IL-4 and P2RX7 in the AD group ( rs = 0.42, 0.40, P = 0.024, 0.034, respectively), while there were no correlations between TGM2 mRNA expression and AD severity-related indicators (all P>0.05), such as age (21[16, 29] years), course of disease (4[1,10] years), eosinophil counts (0.33[0.18, 0.65] × 10 9/L), basophil counts (0.04[0.03, 0.06] × 10 9/L], SCORAD scores (60.5[46.98, 66.13] points), and serum total IgE levels (373 [40, 1 815] IU/ml). The relative protein expression levels of TGM2 on the surface of PBMCs did not differ between the AD group and control group (54.9 [47.6, 62.8] vs. 55.55 [51.5, 60.25], U = 112.00, P = 0.922) ], and no correlations were observed between the protein expression of TGM2 on PBMCs and AD severity-related indicators in the AD group (all P > 0.05) . Conclusion:No significant differences were observed in TGM2 mRNA expression in PBMCs or TGM2 protein expression on the surface of PBMCs between the AD patients and healthy controls, and there were no correlations between the TGM2 mRNA and protein expression and AD severity.

Objective: To investigate the relationship among depression, anxiety, stress and addictive substance use behavior in secondary vocational students. Methods: Cluster sampling method and the Adolescent Health-related Behaviors Questionnaire were used to collect demographic characteristics, psychological symptoms, and addictive substance usage among 5 935 students in nine vocational schools in Chongqing, Zhaoqing, Ningbo, and Taiyuan. Multivariate logistic regression analysis was used to analyze the relationship between the addictive substance use behavior and psychological factors. Results: The detection rates of depression, anxiety and stress were 46.5% (n=2 762), 58.7% (n=3 483), and 29.8% (n= 1 770), respectively. The prevalence of addictive substances was 74.8% (n=4 440), traditional drugs was 0.8% (n=50), new drugs was 2.8% (n=166), other addictive drugs was 4.1% (n=241). Multivariate logistic regression analysis showed that compared with the normal psychological states of secondary vocational students, the OR value of mild depression tendency alcohol and tobacco use behavior of secondary vocational students was 1.45; the OR values of mild anxiety, moderate anxiety, severe anxiety and very serious anxiety were 1.46, 1.46, 1.71, and 1.83, respectively; the traditional drugs use behaviors were 5.51, and 2.61, respectively, for the severe anxiety and very serious anxiety. Compared with the normal psychological state of secondary vocational students, the OR values of the severe anxiety and very severe anxiety were 2.56, and 2.66, respectively, for severe anxiety and very serious anxiety. Compared with normal psychological status of secondary vocational students, the OR values of mild, moderate, severe, and very severe anxiety were 2.14, 2.47, 2.39, and 3.45, respectively; all P values <0.05. Conclusion Anxiety and mild depression were risk factors of tobacco and alcohol use in secondary vocational students; severe and above anxiety were the risk factors of drug use in secondary vocational students; anxiety was the risk factor for other addictive drug use in secondary vocational students.